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Analisis Jangkauan Kendaraan Listrik Menggunakan Teknik Regresi Studi Kasus Kendaraan Listrik Universitas Mataram Mabrur, Muh. Hijjul Mabrur; Okariawan, I Dewa Ketut; I Made , Mara
Jurnal Teknik Mesin Mechanical Xplore Vol 5 No 2 (2024): Jurnal Teknik Mesin Mechanical Xplore (JTMMX)
Publisher : Mechanical Engineering Department Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jtmmx.v5i2.8861

Abstract

The development of electric vehicles (EV) represents a strategic approach to reducing carbon emissions and decreasing reliance on fossil fuels. This study analyzes the driving range of electric vehicles at the University of Mataram using regression techniques to examine the relationship between vehicle load, energy consumption, and range efficiency. Field tests were conducted under various vehicle load conditions (120.5 kg, 130.5 kg, and 140.5 kg) and gear ratio variations. A linear regression analysis was applied to determine the influence of independent variables (vehicle load and gear ratio) on the dependent variables (energy consumption and driving range). The results indicate a positive correlation between vehicle load and energy consumption, alongside a negative correlation with driving range. Specifically, at a load of 120.5 kg, energy consumption was recorded at 29.29 Wh/km, achieving a maximum range efficiency of 82.82 km per kWh. In contrast, at 140.5 kg, energy consumption increased to 44.00 Wh/km, while range efficiency declined to 54.56 km per kWh. Additionally, gear ratio variations significantly affected vehicle performance, with a gear ratio of 10.29 yielding the highest range efficiency of 112.55 km per kWh, whereas a gear ratio of 6.43 exhibited lower efficiency. These findings emphasize the critical role of vehicle load management and optimal gear ratio selection in enhancing energy efficiency. The study provides valuable insights for the design and development of more efficient and sustainable electric vehicles, contributing to advancements in EV technology.
Analisis Jangkauan Kendaraan Listrik Menggunakan Teknik Regresi Studi Kasus Kendaraan Listrik Universitas Mataram Mabrur, Muh. Hijjul Mabrur; Okariawan, I Dewa Ketut; I Made , Mara
Jurnal Teknik Mesin Mechanical Xplore Vol. 5 No. 2 (2024): Jurnal Teknik Mesin Mechanical Xplore (JTMMX)
Publisher : Mechanical Engineering Department Universitas Buana Perjuangan Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36805/jtmmx.v5i2.8861

Abstract

The development of electric vehicles (EV) represents a strategic approach to reducing carbon emissions and decreasing reliance on fossil fuels. This study analyzes the driving range of electric vehicles at the University of Mataram using regression techniques to examine the relationship between vehicle load, energy consumption, and range efficiency. Field tests were conducted under various vehicle load conditions (120.5 kg, 130.5 kg, and 140.5 kg) and gear ratio variations. A linear regression analysis was applied to determine the influence of independent variables (vehicle load and gear ratio) on the dependent variables (energy consumption and driving range). The results indicate a positive correlation between vehicle load and energy consumption, alongside a negative correlation with driving range. Specifically, at a load of 120.5 kg, energy consumption was recorded at 29.29 Wh/km, achieving a maximum range efficiency of 82.82 km per kWh. In contrast, at 140.5 kg, energy consumption increased to 44.00 Wh/km, while range efficiency declined to 54.56 km per kWh. Additionally, gear ratio variations significantly affected vehicle performance, with a gear ratio of 10.29 yielding the highest range efficiency of 112.55 km per kWh, whereas a gear ratio of 6.43 exhibited lower efficiency. These findings emphasize the critical role of vehicle load management and optimal gear ratio selection in enhancing energy efficiency. The study provides valuable insights for the design and development of more efficient and sustainable electric vehicles, contributing to advancements in EV technology.